Skip to main content

A multilevel prediction method for predicting interactions between bacteriophages and pathogenic bacterial hosts

Project description

###PhageTB

PhageTB is a multilevel prediction method for predicting interactions between bacteriophages and pathogenic bacterial hosts. This study develops a novel host prediction method for predicting hosts of query phages by their genome sequences utilizing alignment-based and alignment-free features.

================================================================================

###nstallation

To install the package, type the following command:

pip install phagetb

================================================================================

###Getting Started

This project is hosted on PhageTB and can be accessed by clicking on the link above or can be used as a standalone application by downloading the source code from this GitHub repository.

There are 3 prediction methods available in this model.

  1. Predict The Bacterial Host For A Query Phage (model.py (phagetb))

This Module Allows Users To Predict The Bacterial Hosts Corresponding To The Query Phages using the genome sequence of the phage.

  1. Predict The Lytic Phage For Query Bacteria (model_bacteria.py (phagetb_1))

This Module Allow Users To Predict The Target Phage Likely To Infect Query Bacteria.

  1. Predict Interaction Of Query Phage-Bacteria Pair (model_phage_host_pair.py (phagetb_2))

This Module Allows Users To Predict Whether Given Phage And Bacterial Hosts Are Likely To Interact With One Another. The prediction from this module for the phage is used as a query for the BLAST task (blastn) against the query bacterial host. The BLAST task is performed using the NCBI BLAST+ tool. The BLAST output is parsed, and if the predicted host and query host have a similarity higher than the threshold, then the phage-host pair is predicted to interact.

================================================================================

###Minimum Usage

Following is the complete list of all options (with default values) that can be used to run the model. you may get these options by " phagetb -h" (and similarly for other modules).

================================================================================

  1. model.py (phagetb)

usage: phagetb [-h] -i INPUT [-o OUTPUT] [-l LEVELS [LEVELS ...]]

Please provide the following arguments

optional arguments:

-h, --help show this help message and exit

-i INPUT, --input INPUT

                    Input: genome sequence of the phage in FASTA format or

                    single sequence per line in single letter code

-o OUTPUT, --output OUTPUT

                    Output: File for saving results by default outfile.csv

-l LEVELS [LEVELS ...], --levels LEVELS [LEVELS ...]

                    Levels: 1: Blast against phage reference DB, 2: Blast
                    against host reference DB, 3: Integrated model, 4:
                    CRISPR by default level is 1

================================================================================

  1. model_bacteria.py (phagetb_1)

usage: phagetb_1 [-h] -i INPUT [-o OUTPUT] [-l LEVELS [LEVELS ...]] [-n NUM_OF_REF_HOSTS] [-t THRESHOLD] [--only_blast]

Please provide the following arguments

optional arguments:

-h, --help show this help message and exit

-i INPUT, --input INPUT

                    Input: genome sequence of the bacteria in FASTA format
                    or single sequence per line in single letter code

-o OUTPUT, --output OUTPUT

                    Output: File for saving results by default outfile.csv

-l LEVELS [LEVELS ...], --levels LEVELS [LEVELS ...]

                    Levels: 1: Blast against phage reference DB, 2: Blast
                    against host reference DB, 3: Integrated model, 4:
                    CRISPR by default level is 1

-n NUM_OF_REF_HOSTS, --num_of_ref_hosts NUM_OF_REF_HOSTS

                    Number of reference hosts to consider by default number is 1

-t THRESHOLD, --threshold THRESHOLD

                    Threshold: evalue threshold for similarity score by default e-value threshold is 0.01

================================================================================

  1. model_phage_host_pair.py (phagetb_2)

usage: phagetb_2 [-h] -v INPUT_PHAGE -b INTPUT_BACTERIA [-o OUTPUT] [-l LEVELS [LEVELS ...]] [-t THRESHOLD]

Please provide the following arguments

optional arguments:

-h, --help show this help message and exit

-v INPUT_PHAGE, --input_phage INPUT_PHAGE

                    Input: genome sequence of the phage in FASTA format or

                    single sequence per line in single letter code

-b INTPUT_BACTERIA, --intput_bacteria INTPUT_BACTERIA

                    Input: genome sequence of the bacteria in FASTA format
                    or single sequence per line in single letter code

-o OUTPUT, --output OUTPUT

                    Output: File for saving results by default outfile.csv

-l LEVELS [LEVELS ...], --levels LEVELS [LEVELS ...]

                    Levels: 1: Blast against phage reference DB, 2: Blast
                    against host reference DB, 3: Integrated model, 4:
                    CRISPR by default level is 1

-t THRESHOLD, --threshold THRESHOLD

                    Threshold: e-value threshold for similarity score by default e-value threshold is 0.01

================================================================================

###File descriptions

  1. blastdb: The database of the hosts, phages and CRISPR sequences.
  2. blast_binaries: The directory contains blastn to execute the similarity search for different OS.
  3. base: The directory containing the extra files and pretrained model required for predictions.
  4. model.py: The Python script for predicting hosts.
  5. model_bacteria.py: The Python script for predicting target phages for a bacteria.
  6. model_phage_host_pair.py: The Python script for predicting interaction for a phage and host pair.
  7. genome_data: The directory containing the genome data of reference hosts

================================================================================

###Address for contact

In case of any queries, feel free to reach out to us at

Prof. G. P. S. Raghava, Head Department of Computational Biology,Indraprastha Institute of Information Technology (IIIT), Okhla Phase III, New Delhi 110020 ; Phone:+91-11-26907444; Email: raghava@iiitd.ac.in Web: http://webs.iiitd.edu.in/raghava/

Reference: Aggarwal et al. (2023) An ensemble method for prediction of phage-based therapy against bacterial infections. Front. Microbiol., DOI: https://doi.org/10.3389/fmicb.2023.1148579

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

phagetb-1.6.tar.gz (34.2 MB view details)

Uploaded Source

Built Distribution

phagetb-1.6-py3-none-any.whl (34.4 MB view details)

Uploaded Python 3

File details

Details for the file phagetb-1.6.tar.gz.

File metadata

  • Download URL: phagetb-1.6.tar.gz
  • Upload date:
  • Size: 34.2 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.7

File hashes

Hashes for phagetb-1.6.tar.gz
Algorithm Hash digest
SHA256 9767acca8a75c19f7963bd6e9e836b2ef9128b3b23aa18403749bbaf4d9c6174
MD5 21a4eac6b2738f69b8b49c4df3f748fe
BLAKE2b-256 44279bde64dda243f8e49e657e47782738a32e41edec8778284dc49ae545376a

See more details on using hashes here.

File details

Details for the file phagetb-1.6-py3-none-any.whl.

File metadata

  • Download URL: phagetb-1.6-py3-none-any.whl
  • Upload date:
  • Size: 34.4 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.7

File hashes

Hashes for phagetb-1.6-py3-none-any.whl
Algorithm Hash digest
SHA256 2a092084d1b22c5449cb3f529c5f5dd7fd1cdd2e31392ec364065433687bc90c
MD5 239c7c1d46c47999006281370658e913
BLAKE2b-256 713cf358f677536a71ac2d5c055fed2abff6c6cdb32a32149a01f024de7fa3af

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page